2007Climatic and Environmental ResearchRequires access

Study on Spatial Interpolation of Snow Depth from Observatories in Western China

Guoan Tang

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Abstract

The spatial interpolation methods are utilized for study on spatial distribution of snow depth from 110 observatories in the west of China.Both the results of ordinary Kriging and Cokriging represent the spatial structure of snow depth distribution,according to the reality.However,the accuracy of Cokriging is higher than Kriging and the result of Cokrigng reflects local characteristics better.The main reasons which affect the precision are the small number of observatories and their asymmetric spatial distribution.The precision of spatial interpolation can be improved through reasonable design of sampling,suitably selecting interpolation methods,and considering the influencing factors of snow distribution,such as terrain and climate.

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What this paper is about

The spatial interpolation methods are utilized for study on spatial distribution of snow depth from 110 observatories in the west of China.Both the results of ordinary Kriging and Cokriging represent the spatial structure of snow depth distribution,according to the reality.However,the accuracy of Cokriging is higher than Kriging and the result of Cokrigng reflects local characteristics better.The main reasons which affect the precision are the small number of observatories and their asymmetric spatial distribution.The precision of spatial interpolation can be improved through reasonable design of sampling,suitably selecting interpolation methods,and considering the influencing factors of snow distribution,such as terrain and climate.

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Available abstract

The spatial interpolation methods are utilized for study on spatial distribution of snow depth from 110 observatories in the west of China.Both the results of ordinary Kriging and Cokriging represent the spatial structure of snow depth distribution,according to the reality.However,the accuracy of Cokriging is higher than Kriging and the result of Cokrigng reflects local characteristics better.The main reasons which affect the precision are the small number of observatories and their asymmetric spatial distribution.The precision of spatial interpolation can be improved through reasonable design of sampling,suitably selecting interpolation methods,and considering the influencing factors of snow distribution,such as terrain and climate.

Key concepts: Kriging, Multivariate interpolation, Snow, Interpolation (computer graphics), Spatial distribution, Terrain, Spatial variability, Environmental science

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